map.datasets | R Documentation |
This function maps a list of datasets through EntrezGene IDs in order to get the union of the genes.
map.datasets(datas, annots, do.mapping = FALSE, mapping.coln = "EntrezGene.ID", mapping, verbose = FALSE)
datas |
List of matrices of gene expressions with samples in rows and probes in columns, dimnames being properly defined. |
annots |
List of matrices of annotations with at least one column named "EntrezGene.ID", dimnames being properly defined. |
do.mapping |
TRUE if the mapping through Entrez Gene ids must be performed (in case of ambiguities, the most variant probe is kept for each gene), FALSE otherwise. |
mapping.coln |
Name of the column containing the biological annotation to be used to map the different datasets, default is "EntrezGene.ID". |
mapping |
Matrix with columns "EntrezGene.ID" and "probe.x" used to force the mapping such that the probes of platform x are not selected based on their variance. |
verbose |
TRUE to print informative messages, FALSE otherwise. |
In case of several probes representing the same EntrezGene ID, the most variant is selected if mapping is not specified. When a EntrezGene ID does not exist in a specific dataset, NA values are introduced.
A list with items:
datas: List of datasets (gene expression matrices)
annots: List of annotations (annotation matrices)
# load VDX dataset data(vdxs) # load NKI dataset data(nkis) # reduce datasets ginter <- intersect(annot.vdxs[ ,"EntrezGene.ID"], annot.nkis[ ,"EntrezGene.ID"]) ginter <- ginter[!is.na(ginter)][1:30] myx <- unique(c(match(ginter, annot.vdxs[ ,"EntrezGene.ID"]), sample(x=1:nrow(annot.vdxs), size=20))) data2.vdxs <- data.vdxs[ ,myx] annot2.vdxs <- annot.vdxs[myx, ] myx <- unique(c(match(ginter, annot.nkis[ ,"EntrezGene.ID"]), sample(x=1:nrow(annot.nkis), size=20))) data2.nkis <- data.nkis[ ,myx] annot2.nkis <- annot.nkis[myx, ] # mapping of datasets datas <- list("VDX"=data2.vdxs,"NKI"=data2.nkis) annots <- list("VDX"=annot2.vdxs, "NKI"=annot2.nkis) datas.mapped <- map.datasets(datas=datas, annots=annots, do.mapping=TRUE) str(datas.mapped, max.level=2)
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